Concepts and Paradigms for Neuromorphic Programming

The value of neuromorphic computers depends crucially on our ability to program them for relevant tasks. Currently, neuromorphic computers are mostly limited to machine learning methods adapted from deep learning. However, neuromorphic computers have potential far beyond deep learning if we can only make use of their computational properties to harness their full power. Neuromorphic programming will necessarily be different from conventional programming, requiring a paradigm shift in how we think about programming in general. The contributions of this paper are 1) a conceptual analysis of what "programming" means in the context of neuromorphic computers and 2) an exploration of existing programming paradigms that are promising yet overlooked in neuromorphic computing. The goal is to expand the horizon of neuromorphic programming methods, thereby allowing researchers to move beyond the shackles of current methods and explore novel directions

Automated Architecture Design for Deep Neural Networks

Machine learning has made tremendous progress in recent years and received large amounts of public attention. Though we are still far from designing a full artificially intelligent agent, machine learning has brought us many applications in which computers solve human learning tasks remarkably well. Much of this progress comes from a recent trend within machine learning, called deep learning. Deep learning models are responsible for many state-of-the-art applications of machine learning. Despite their success, deep learning models are hard to train, very difficult to understand, and often times so complex that training is only possible on very large GPU clusters. Lots of work has been done on enabling neural networks to learn efficiently. However, the design and architecture of such neural networks is often done manually through trial and error and expert knowledge. This thesis inspects different approaches, existing and novel, to automate the design of deep feedforward neural networks in an attempt to create less complex models with good performance that take away the burden of deciding on an architecture and make it more efficient to design and train such deep networks.Comment: Undergraduate Thesi

Dynamic pathway of the photoinduced phase transition of TbMnO3_3

We investigate the demagnetization dynamics of the cycloidal and sinusoidal phases of multiferroic TbMnO$_3$ by means of time-resolved resonant soft x-ray diffraction following excitation by an optical pump. Using orthogonal linear x-ray polarizations, we suceeded in disentangling the response of the multiferroic cycloidal spin order from the sinusoidal antiferromagnetic order in the time domain. This enables us to identify the transient magnetic phase created by intense photoexcitation of the electrons and subsequent heating of the spin system on a picosecond timescale. The transient phase is shown to be a spin density wave, as in the adiabatic case, which nevertheless retains the wave vector of the cycloidal long range order. Two different pump photon energies, 1.55 eV and 3.1 eV, lead to population of the conduction band predominantly via intersite $d$-$d$ transitions or intrasite $p$-$d$ transitions, respectively. We find that the nature of the optical excitation does not play an important role in determining the dynamics of magnetic order melting. Further, we observe that the orbital reconstruction, which is induced by the spin ordering, disappears on a timescale comparable to that of the cycloidal order, attesting to a direct coupling between magnetic and orbital orders. Our observations are discussed in the context of recent theoretical models of demagnetization dynamics in strongly correlated systems, revealing the potential of this type of measurement as a benchmark for such complex theoretical studies

Linearized hydrodynamics from probe-sources in the gauge-string duality

We study the response of an infinite, asymptotically static N=4 plasma to a generic localized source in the probe approximation. At large distances, the energy momentum tensor of the plasma includes a term which satisfies the constitutive relations of linearized hydrodynamics, but it can also include a non-hydrodynamical term which contributes at the same order as viscous corrections, or even at leading order in some cases. The conditions for the appearance of a laminar wake far behind the source and its relevance for phenomenological models used to explain di-hadron correlations are discussed. We also consider the energy momentum tensor near the source, where the hydrodynamical approximation can be expected to break down. Our analysis encompasses a wide range of sources which are localized in the bulk of AdS, including trailing strings, mesonic and baryonic configurations of strings, and point particles.Comment: 43 pages, 3 appendice

A Variational Method in Out of Equilibrium Physical Systems

A variational principle is further developed for out of equilibrium dynamical systems by using the concept of maximum entropy. With this new formulation it is obtained a set of two first-order differential equations, revealing the same formal symplectic structure shared by classical mechanics, fluid mechanics and thermodynamics. In particular, it is obtained an extended equation of motion for a rotating dynamical system, from where it emerges a kind of topological torsion current of the form $\epsilon_{ijk} A_j \omega_k$, with $A_j$ and $\omega_k$ denoting components of the vector potential (gravitational or/and electromagnetic) and $\omega$ is the angular velocity of the accelerated frame. In addition, it is derived a special form of Umov-Poynting's theorem for rotating gravito-electromagnetic systems, and obtained a general condition of equilibrium for a rotating plasma. The variational method is then applied to clarify the working mechanism of some particular devices, such as the Bennett pinch and vacuum arcs, to calculate the power extraction from an hurricane, and to discuss the effect of transport angular momentum on the radiactive heating of planetary atmospheres. This development is seen to be advantageous and opens options for systematic improvements.Comment: 22 pages, 1 figure, submitted to review, added one referenc

The gauge-string duality and heavy ion collisions

I review at a non-technical level the use of the gauge-string duality to study aspects of heavy ion collisions, with special emphasis on the trailing string calculation of heavy quark energy loss. I include some brief speculations on how variants of the trailing string construction could provide a toy model of black hole formation and evaporation. This essay is an invited contribution to "Forty Years of String Theory" and is aimed at philosophers and historians of science as well as physicists.Comment: 21 page